fitRMU: Adjust incomplete timeseries with various constraints.

Description

The data must be a data.frame with the first column being years
and two columns for each beach: the average and the se for the estimate.
The correspondance between mean and se for each rookery are given in the RMU.names data.frame.
In the result list, the mean proportions for each rookeries are in $proportions, $proportions.CI.0.05 and $proportions.CI.0.95.
The names of beach columns must not begin by T_, SD_, a0_, a1_ or a2_ and cannot be r.
A RMU is the acronyme for Regional Managment Unit. See:
Wallace, B.P., DiMatteo, A.D., Hurley, B.J., Finkbeiner, E.M., Bolten, A.B.,
Chaloupka, M.Y., Hutchinson, B.J., Abreu-Grobois, F.A., Amorocho, D., Bjorndal, K.A.,
Bourjea, J., Bowen, B.W., Dueñas, R.B., Casale, P., Choudhury, B.C., Costa, A.,
Dutton, P.H., Fallabrino, A., Girard, A., Girondot, M., Godfrey, M.H., Hamann, M.,
López-Mendilaharsu, M., Marcovaldi, M.A., Mortimer, J.A., Musick, J.A., Nel, R.,
Seminoff, J.A., Troëng, S., Witherington, B., Mast, R.B., 2010. Regional
management units for marine turtles: a novel framework for prioritizing
conservation and research across multiple scales. PLoS One 5, e15465.
Variance for each value is additive based on both the observed SE (in the RMU.data
object) and a constant value dependent on the rookery when model.SD is equal to
"beach-constant". The value is a global constant when model.SD is "global-constant".
The value is proportional to the observed number of nests when model.SD is
"global-proportional" with aSD_*observed+SD_ with aSD_ and SD_ being fitted
values. This value is fixed to zero when model.SD is "Zero".